title: Multi-conformation dynamic pharmacophore modeling of the peroxisome proliferator-activated receptor γ for the discovery of novel agonists.
abstract: Activation of the peroxisome proliferator-activated receptor γ (PPARγ) is important for the treatment of type 2 diabetes and obesity through the regulation of glucose metabolism and fatty acid accumulation. Hence, the discovery of novel PPARγ agonists is necessary to overcome these diseases. In this study, a newly developed approach, multi-conformation dynamic pharmacophore modeling (MCDPM), was used for screening candidate compounds that can properly bind PPARγ. Highly populated structures obtained from molecular dynamics (MD) simulations were selected by clustering analysis. Based on these structures, pharmacophore models were generated from the ligand-binding pocket and then validated to check the rationality. Consequently, two hits were retrieved as final candidates by utilizing virtual screening and molecular docking simulations. These compounds can be used in the design of novel PPARγ agonists.
authors.affiliation: Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.
authors.forename: Young-sik
authors.initials: YS
authors.lastname: Sohn
authors.forename: Chanin
authors.initials: C
authors.lastname: Park
authors.forename: Yuno
authors.initials: Y
authors.lastname: Lee
authors.forename: Songmi
authors.initials: S
authors.lastname: Kim
authors.forename: Sundarapandian
authors.initials: S
authors.lastname: Thangapandian
authors.forename: Yongseong
authors.initials: Y
authors.lastname: Kim
authors.forename: Hyong-Ha
authors.initials: HH
authors.lastname: Kim
authors.forename: Jung-Keun
authors.initials: JK
authors.lastname: Suh
authors.forename: Keun Woo
authors.initials: KW
authors.lastname: Lee
mesh_terms: D020816:Amino Acid Motifs; D001665:Binding Sites; D016000:Cluster Analysis; D055808:Drug Discovery; D006801:Humans; D006860:Hydrogen Bonding; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D047495:PPAR gamma / Q000819:agonists / Q000737:chemistry*; D011485:Protein Binding; D000077154:Rosiglitazone; D054852:Small Molecule Libraries; D045162:Thiazolidinediones / Q000737:chemistry
chemical_list: D047495:PPAR gamma; D054852:Small Molecule Libraries; D045162:Thiazolidinediones; D000077154:Rosiglitazone
keywords: Drug design; Molecular dynamics simulation; Multi-conformation dynamic pharmacophore modeling; Peroxisome proliferator-activated receptor γ; Type 2 diabetes